Color has a significant impact on our life experience. It influences nearly all of our buying decisions and affects our mood and emotional state. People are often in situations where they are choosing products based on color, such as choosing paint colors for a room, choosing decorative items for a home or office, buying clothes, and so forth. Despite the significant impact that color has on all of our experiences, many people feel overwhelmed by color-related buying decisions and rightly so. There are millions of colors, and a nearly infinite number of combinations that can be created with those colors. In this sea of color, it is difficult for a person to define which colors he or she is drawn to or to select a palette of colors that coordinate with one another.
Both brick-and-mortar and online retailers are trying to find ways to help customers make color-related buying decisions, particularly in industries such as home décor  and fashion where color is one of the top buying considerations. The challenge is that there is no coherence between the colors or selection processes of various retailers, so if a customer is remodeling the customer's house he or she would need to choose from a unique set of colors and utilize different color selection “tools” for every retailer from which the customer purchases. This slows down the decision-making process for the customer and lowers the retailers' average sale and closing rate.
Past attempts to solve these problems typically include some variation of applying traditional color theory to select coordinating colors (e.g., from a color wheel). This process is finite, leading to only a small subset of locked color variations, and fails to take into account more subtle nuances of color, such as hue, chroma, saturation, and so forth. In addition, such systems typically ask the user to identify a small set of colors with which the user wants to coordinate, but life is rich in color, and it can be difficult for the user to know which set of colors to choose. For example, a simple couch may have dozens of colors in its fabric, and if the user is trying to coordinate with this or another item, the user may be unskilled at the task of identifying the main colors evoked by an item. In addition, such systems do not provide any level of shared knowledge. In other words, users cannot view results that other users have produced to see if they might like the same colors. Using the previous example, maybe someone else that purchased the same couch has already chosen a good coordinating wall color, but there is no way for a later purchaser of the same item to know that.